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    <title>links.lmorchard.com - #concurrency</title>
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    <lastBuildDate>Mon, 02 Nov 2026 08:24:51 +0000</lastBuildDate>
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      <title>How Much Memory Do You Need in 2024 to Run 1 Million Concurrent Tasks?</title>
      <link>https://hez2010.github.io/async-runtimes-benchmarks-2024/</link>
      <description>Finally, C# undoubtedly beat all other languages; it&#39;s very competitive and has really become a monster. And as expected, Rust continues to do a good job on memory efficiency.&#xD;&#xA;&#xD;&#xA;The distance between Go and the others increased. Now Go loses by over 13 times to the winner. It also loses by over 2 times to Java, which contradicts the general perception of the JVM being a memory hog and Go being lightweight.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #concurrency #csharp #dev #golang #rust&lt;/p&gt;</description>
      <pubDate>Fri, 29 Nov 2024 02:10:22 +0000</pubDate>
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      <category>concurrency</category>
      <category>csharp</category>
      <category>dev</category>
      <category>golang</category>
      <category>rust</category>
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      <title>Pin and suffering</title>
      <link>https://fasterthanli.me/articles/pin-and-suffering</link>
      <description>I&#39;d like to think that my understanding of &#34;async Rust&#34; has increased over the past year or so. I&#39;m 100% onboard with the basic principle: I would like to handle thousands of concurrent tasks using a handful of threads. That sounds great!&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #async #concurrency #imported:pinboard #programming #rust&lt;/p&gt;</description>
      <pubDate>Sun, 23 Jul 2023 20:22:27 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:39</guid>
      <category>async</category>
      <category>concurrency</category>
      <category>imported:pinboard</category>
      <category>programming</category>
      <category>rust</category>
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      <title>Parallelism in one line — Building Things on the Internet — Medium</title>
      <link>https://medium.com/building-things-on-the-internet/40e9b2b36148</link>
      <description>Parallel versions of the map function are provided by two libraries: multiprocessing, and also its little known, but equally fantastic step child: multiprocessing.dummy.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #algorithms #concurrency #dev #imported:pinboard #parallel #python&lt;/p&gt;</description>
      <pubDate>Wed, 29 Jan 2014 14:57:57 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:24521</guid>
      <category>algorithms</category>
      <category>concurrency</category>
      <category>dev</category>
      <category>imported:pinboard</category>
      <category>parallel</category>
      <category>python</category>
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      <title>Concurrency in JavaScript | TypedArray.org</title>
      <link>http://typedarray.org/concurrency-in-javascript/</link>
      <description>Web Workers are now broadly available in most browsers even on mobile (caniuse.com stats for Web Workers) and give you the power of concurrency from within JavaScript. It will allow you to move expensive computations to other threads, to permit best responsive programming, and ideally open the doors in the future to true parallelization in JavaScript. Let’s have a look at the reasons why you may be interested into leveraging Web Workers.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #concurrency #imported:pinboard #javascript #webdev #webworkers&lt;/p&gt;</description>
      <pubDate>Fri, 12 Jul 2013 13:24:15 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:32246</guid>
      <category>concurrency</category>
      <category>imported:pinboard</category>
      <category>javascript</category>
      <category>webdev</category>
      <category>webworkers</category>
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    <item>
      <title>Concurrency in JavaScript | TypedArray.org</title>
      <link>http://typedarray.org/concurrency-in-javascript</link>
      <description>Web Workers are now broadly available in most browsers even on mobile (caniuse.com stats for Web Workers) and give you the power of concurrency from within JavaScript. It will allow you to move expensive computations to other threads, to permit best responsive programming, and ideally open the doors in the future to true parallelization in JavaScript. Let’s have a look at the reasons why you may be interested into leveraging Web Workers.&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #concurrency #javascript #webdev #webworkers&lt;/p&gt;</description>
      <pubDate>Fri, 12 Jul 2013 13:24:15 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:23899</guid>
      <category>concurrency</category>
      <category>javascript</category>
      <category>webdev</category>
      <category>webworkers</category>
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    <item>
      <title>Google Research Publications - MapReduce: Simplified Data Processing on Large Clusters</title>
      <link>http://labs.google.com/papers/mapreduce.html</link>
      <description>&#34;MapReduce is a programming model and an associated implementation for processing and generating large data sets.&#34;&lt;br/&gt;&#xA;&lt;p&gt;&lt;strong&gt;Tags:&lt;/strong&gt; #algorithms #compsci #concurrency #google&lt;/p&gt;</description>
      <pubDate>Sun, 01 Jan 2006 16:58:39 +0000</pubDate>
      <guid isPermaLink="false">linkding-ssg:bookmark:5983</guid>
      <category>algorithms</category>
      <category>compsci</category>
      <category>concurrency</category>
      <category>google</category>
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